Enhanced Color Nighttime Light Remote Sensing Imagery Using Dual-Sampling Adjustment.

Area of Science:

• Remote Sensing
• Geospatial Analysis
• Urban Studies

Background:

• Nighttime light remote sensing imagery suffers from low spatial resolution and single-band limitations, hindering accurate ground information capture.
• Existing methods struggle to effectively fuse day and night remote sensing data, limiting the quality of derived products.

Purpose of the Study:

• To enhance nighttime light remote sensing imagery by fusing it with daytime optical images.
• To generate high-quality color nighttime light remote sensing imagery with improved spatial resolution and feature retention.
• To develop a visual tool for assessing urban economic vitality using enhanced nighttime light data.

Main Methods:

• A dual-sampling adjustment method was proposed for fusing daytime optical images with nighttime light remote sensing imagery.
• The fusion process aimed to enhance spatial resolution from 500 m to 15 m.
• Quality evaluations were conducted to assess optical fidelity and spatial texture features of the enhanced imagery.

Main Results:

• The spatial resolution of fused images was significantly improved to 15 m, retaining both ground features and nighttime light distribution.
• Quality evaluations confirmed the dual-sampling adjustment effectively balances optical fidelity and spatial texture.
• Color nighttime light brightness in Beijing's CBD showed a strong correlation (r = 0.7221 in Dongcheng District) with business activity.

Conclusions:

• The proposed dual-sampling adjustment method overcomes limitations in fusing day-night remote sensing imagery.
• The generated color nighttime light remote sensing imagery expands application fields and provides decision support for refined urban management.
• Enhanced nighttime light data offers a visual tool for assessing urban economic vitality and supporting refined urban management.